As traffic visual recognition is the prerequisite for traffic flow prediction, some researchers also involved perception systems in the field. The key to such system enhancement is whether each vehicle can be accurately recognized. The authors of [1]} come up with an edge-computing framework that utilizes the real-time multi-object detection and tracking algorithms to provide the inputs to the traffic flow prediction. As cooperative perception system can largely enhance the perceiving range and help see through occlusions [2]}, [3]}, [4]},the authors of [5]} integrate cooperative perception concept with traffic prediction together to better estimate the traffic states. Similarly, the authors of [6]} study how to boost the traffic state estimation accuracy by enhancing the perception performance under a partially connected vehicle environment.
